Pith. sign in

REVIEW 3 major objections 7 minor 82 references

SpectraMatcher: A Python Program for Interactive Analysis and Peak Assignment of Vibronic Spectra

T0 review · 3 major / 7 minor · reviewed 2026-08-15 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗ Review JSON

Pith's one-line read SpectraMatcher is a GUI that automates matching experimental and computed vibronic spectra.

desk verdict A credible open-source GUI for vibronic peak matching that does what it claims, with the one novel heuristic (automatic mode classification) being the soft spot. read the letter →

arxiv 2505.09060 v1 pith:32FWS6TP submitted 2025-05-14 physics.chem-ph physics.bio-phphysics.comp-ph

Johanna Langner , Isabelle Weber , Henryk A. Witek , Yuan-Pern Lee This is my paper · ORCID
classification physics.chem-phphysics.bio-phphysics.comp-ph
keywords vibronicspectroscopypeakmatchinganharmoniccorrectionvibrationalfrequencyscalefactorsconvolutionspectrumanalysisfluorescencegraphicaluserinterface
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

SpectraMatcher is a cross-platform desktop program, written in Python, that brings the comparison of experimental and computed vibronic spectra into an interactive graphical interface. The paper's central claim is that the whole workflow—importing quantum-chemistry output, detecting peaks in a measured spectrum, adjusting line width, zero-zero energy, and intensity, and assigning computed transitions to observed peaks—can be automated and steered visually, with no scripting required. The paper argues this matters because manual peak assignment in large molecules with densely overlapping vibronic bands is slow and error-prone. A demonstration on ovalene concludes that the measured emission spectrum is best described by the simulated S2→S0 emission spectrum, showing the tool being used to settle an excited-state assignment.

What carries the argument

The load-bearing mechanism is the combination of an automatic mode-type classifier and an intensity-prioritized matcher. Each vibrational mode is classified as an out-of-plane bend, an X–H stretch, or "other" by geometric rules on its displacement vector; that class determines the scaling factor $f_{\tau(m)}$ applied in the corrected-wavenumber formula $\tilde{\nu}_t = \sum_{m} f_{\tau(m)} v_m \tilde{\nu}_m$. The matcher greedily assigns the most intense computed peaks to experimental peaks satisfying $|x_c - x_e| < \tau_{\Delta\tilde{\nu}}$ and an intensity-ratio threshold, selecting among candidates by the score $y_e/(x_c-x_e)^2$. These heuristics are what let the program update an entire assignment table in real time while the user drags parameters.

What would settle it

Take a molecule with independently known mode types (e.g., from a high-level anharmonic calculation or a high-resolution experimental assignment), import its frequency output and experimental spectrum into SpectraMatcher, and compare the program's automatic mode-type flags and scaled peak positions with the known values; the central claim fails in its practical form if any mislabeled mode moves a peak by more than the default 30 cm$^{-1}$ matching threshold, because the assignment would then be silently wrong.

Watch

Extended reading notes

Core claim

The paper's central claim is a practical software construction: a program that turns two kinds of input—a list of Franck–Condon/Herzberg–Teller transitions with their vibrational mode labels, and a raw experimental spectrum—into an aligned, assigned, exportable result. To do this it computes theoretical stick spectra, adjusts each computed peak's wavenumber by a per-mode-type scaling factor, convolves the sticks with a Lorentzian profile, and then matches computed peaks to detected experimental peaks in order of decreasing intensity using a wavenumber-distance threshold, an intensity-ratio threshold, and a score that prefers intense, close peaks. The case study uses the program to compare six simulated excited-state emission spectra of ovalene with the measured para-hydrogen spectrum; SpectraMatcher's composite-spectrum overlay and auto-generated assignment table support the conclusion that the spectrum belongs to the S2→S0 transition rather than the previously proposed S1→S0 transition.

Load-bearing premise

The central load-bearing premise is that the automatic rules for classifying vibrations as out-of-plane bends or X–H stretches—thresholds tested only on planar aromatic hydrocarbons—apply correctly to any molecule the user analyzes; if they misclassify a mode, the wrong scaling factor is applied and peaks shift without any warning.

Editorial extensions

If this is right

  • A spectroscopist can turn a raw experimental trace and quantum-chemistry output into a publication-ready assignment table and figure, with all alignment steps recorded in a project file.
  • For molecules whose spectra mix transitions from several electronic states, the composite-spectrum overlay makes it possible to disentangle contributions and estimate energy gaps, as done for ovalene's S2 and S3 states.
  • Type-specific anharmonic scaling lets a user correct high-wavenumber X–H stretch bands without moving the rest of the spectrum, matching the known systematic anharmonicity of these modes.
  • Because matching proceeds from the most intense peaks downward, assignments stay anchored on the strongest features even when many weak bands overlap.
  • The default thresholds (30 cm$^{-1}$ distance, 3% intensity ratio) and the symmetric intensity test give a sensible starting point that users can tune per spectrum.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • The planarity and mode-classification thresholds (1 Å, 0.9 squared out-of-plane weight, 0.2 Å H-bond dot product) were tuned on planar PAHs; a natural extension is to re-derive them from the molecular inertia tensor so the same logic applies to non-planar molecules.
  • The matching score $I_{\mathrm{exp}}/\Delta\tilde{\nu}^2$ implicitly sets a trade-off between intensity and wavenumber closeness; in cm$^{-1}$ units, very close weak peaks can outscore farther intense peaks, which may matter for high-resolution spectra and could be tested with synthetic stick spectra.
  • The tool's workflow could be used as a cheap surrogate for full anharmonic calculations: fitted scaling factors for a molecule could be compared against independently computed anharmonic wavenumbers to check whether type-specific scaling captures the correct trends.
  • The ovalene demo, which reassigns the emission to S2→S0, suggests that interactive composite-spectrum tools of this kind can systematically revisit older state assignments for other PAHs with disputed or ambiguous electronic bands.
Share X Bluesky LinkedIn Reddit HN

Signed reviews

No signed human review yet.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 7 minor

Summary. SpectraMatcher is a cross-platform Python GUI for interactively comparing experimental vibronic spectra with simulated Franck–Condon/Herzberg–Teller spectra computed by Gaussian. The manuscript describes the workflow (Sections 3–4): import and validation of Gaussian .log files, automatic detection of peaks in experimental spectra, classification of vibrational modes as out-of-plane bends, X–H stretches, or other modes, Lorentzian convolution of stick transitions (Eqs. (1)–(2)), type-specific wavenumber scaling (Eq. (3)), and automated matching of computed to experimental peaks via proximity and intensity thresholds (Eqs. (4)–(5)) with a scoring function (Eq. (6)). A case study on ovalene (Section 5) illustrates the workflow by reproducing the S2–S0 emission assignment and composing an S2+S3 excitation spectrum. The equations and software design are clearly presented, and the program is openly available with documentation.

Significance. The paper addresses a genuine practical bottleneck: the manual alignment and assignment of vibronic spectra. The proposed tool is open-source, cross-platform, GUI-based, and includes reproducible project files, automated matching, and publication-ready export formats; if validated, it would be useful to experimental spectroscopy groups. The core mathematics is standard and internally consistent; the convolution, scaling, and matching equations are simple and easily audited. The strengths are the clean architecture, the explicit equations, the public code and documentation, and the concrete ovalene demonstration. The main reservations are that the automatic mode-classification heuristic in Section 3.4 is validated only on planar PAHs and that the ovalene case study is an illustration with parameters fitted to the displayed experiment rather than an independent test of matching or classification accuracy.

major comments (3)
  1. [§3.4 and Eq. (3)] The automatic mode classification is load-bearing for the type-specific scaling feature, but the fixed thresholds (planarity via maximum atomic displacement < 1 Å along one Cartesian axis, OOP squared weight > 0.9, X–H bond-aligned displacement dot product > 0.2 Å) are validated only on pyrene, naphthalene, and ovalene, all planar PAHs. Because the classification is consumed automatically in Eq. (3) without user inspection, a misclassified mode receives the wrong scaling factor (in the ovalene demo, fX-H = 0.977 versus fothers = 0.988), shifting the affected transitions by tens of cm−1 and potentially breaking the matching in Eqs. (4)–(5) silently. The paper criticizes the arbitrary wavenumber cutoff of earlier approaches but does not test this replacement on non-planar or differently oriented molecules; moreover, Section 3.2 states that displacement vectors default to two decimal places, so rounding can move a borderline mode across a threshold. I recommend validating the classifier on a diverse test set, using high-precision displacements by default, and exposing the assigned mode type for user override.
  2. [§4.5 and Eq. (6)] The automated matching algorithm is described precisely, but its accuracy is never quantitatively evaluated, and the scoring function has properties that should be addressed. The score in Eq. (6) is unnormalized and has units of cm^2; it divides by zero if x_c = x_e exactly, and it is not invariant to the choice of wavenumber units. Because the algorithm processes computed peaks greedily in descending intensity and removes each matched experimental peak from further consideration, the final assignment set can depend on the order of processing. A concrete test would be to generate synthetic spectra with known true assignments (e.g., by adding noise to a simulated stick spectrum) and report how often Eqs. (4)–(6) recover the ground truth as a function of tau_deltanu, tau_I, and noise level. Without such a benchmark, the central claim that the program 'automates and streamlines' matching is plausible but not substantiated.
  3. [§5 (ovalene case study)] The conclusion that 'our experimental spectrum is best described by the simulated S2 to S0 emission spectrum' is reached after interactively tuning fX-H, fothers, the zero-zero shift, and the Lorentzian width against that same experimental spectrum. As a demonstration of the GUI this is acceptable, but as evidence for the program's assignment capability it is partly circular. A concrete test would be to apply the workflow with default thresholds and without per-spectrum tuning of scaling factors to a molecule with a known assignment, such as pyrene or naphthalene, and report whether the correct electronic state is recovered; alternatively, the text should state explicitly that the section reproduces the assignment of reference [36] rather than validating the tool.
minor comments (7)
  1. [Program Summary] The sentence 'Automatic spectral feature detection is performed on experimental data via to facilitate the analysis' contains a missing word after 'via'; it should be reworded.
  2. [§5 and Table 1] The text refers to 'Table 5' when referring to the auto-generated assignment table, but the table in the manuscript is labeled 'Table 1'; the numbering should be made consistent.
  3. [§3.7 and §4.5] The scoring function is introduced in Section 3.7 as 'Iexp/Δν^2' and defined in Eq. (6); the two presentations should be reconciled, and the case Δν = 0 should be handled explicitly.
  4. [§4.4] The seven-point moving average filter is a fixed choice for peak detection; the paper should either justify this choice or make the window size user-configurable.
  5. [§3.4] The thresholds for planarity, OOP weight, and X–H dot product are stated without any sensitivity information; a short analysis of how many ovalene modes lie near these thresholds would help users understand the risk of misclassification.
  6. [Introduction and Program Summary] The restriction that only Gaussian 16 output files are supported appears in the Program Summary but not in the Introduction; this scope limitation should be stated earlier, since it affects reader expectations.
  7. [Eq. (5)] The intensity criterion min(y_c/y_e, y_e/y_c) > tau_I with the default tau_I = 0.03 permits a computed peak to match an experimental peak whose intensity differs by as much as a factor of 33; the term 'relative intensity threshold' may mislead users, so the text should clarify this behavior.

Circularity Check

1 steps flagged · score 2.0 of 10

Mild, localized circularity in the ovalene case study: the X-H stretch band is positioned by a factor fitted to the experimental peak and then reported as a predicted matching feature; the software's central tool claim is otherwise independent.

  1. fitted input called prediction [Section 5 (Case study) and Table 1 caption]
    "'The simulation also predicts contributions from fundamental C–H stretching vibrations around 3100 cm−1. Leveraging SpectraMatcher’s support for vibration type specific wavenumber scaling, we selectively adjusted the position of the predicted 3100 cm−1 band by setting the scaling factor for X–H stretches to 0.977, thereby further improving the alignment of experimental and simulated data.' Table 1: 'The vibrational frequency scaling factors applied here are fX-H = 0.977 for X-H stretching modes (most notably adjusting the peak at 3092 cm−1 to fit the experiment) and fothers = 0.988.'"

    The corrected position of the C-H stretching band is computed by Eq. (3) as fX-H times the harmonic wavenumber, and fX-H=0.977 is selected specifically so that the 3167.6/3168.3 cm−1 harmonic modes land near the 3092–3095 cm−1 experimental feature. The paper itself says the factor was set 'to fit the experiment.' Therefore the subsequent appearance of a matched 3095.4 cm−1 peak in Table 1 and Fig. 2 is not an independent confirmation of the simulated X-H band; it is an indication that the fitted parameter was chosen to reproduce that feature. The qualitative prediction of a C-H stretching band near 3100 cm−1 remains independent, but the precise predicted position used in the match is constructed from the experimental datum it is matched against.

full rationale

The central claim of the paper is a tool claim: SpectraMatcher imports Gaussian FC/HT output and experimental spectra, applies user-defined scaling and convolution, detects peaks, and matches them by proximity and intensity thresholds. That claim is testable by running the public code and is not circular. The mode-classification thresholds in Section 3.4 are empirical heuristics with limited validation, but they are not defined in terms of the spectral outcome and therefore are a correctness/robustness concern, not a circularity. The ovalene case study does contain one partially circular element: the X-H scaling factor is fitted to the experimental 3092 cm−1 band, and the resulting corrected peak is then presented among the matched assignments. Because Eq. (3) multiplies the harmonic wavenumber by this user-chosen factor, the match at 3095.4 cm−1 is forced by the fit rather than independently predicted. The S2-versus-S1 assignment itself is inherited transparently from the authors' prior work (Ref. [36]), which is external peer-reviewed evidence; citing it is not in itself circular. Overall, the circularity is minor and localized to the demo, leaving the software's main functionality independent, so the score is 2.

Assumptions & free parameters 5 free parameters · 5 assumptions · 0 invented entities

The software itself rests on standard spectroscopy and signal-processing background, which is cited. The case study carries two fitted scaling factors and a set of hand-chosen classification thresholds that are validated only on planar PAHs; these are the quantities that control the reported agreement.

free parameters (5)
  • f_others (case study scaling factor for 'other' modes) = 0.988
    Applied to all non-X-H, non-OOP modes in the ovalene emission demo; chosen interactively in the GUI to align computed bands with the experimental spectrum (Table 1).
  • f_X-H (case study scaling factor for X-H stretches) = 0.977
    Set to move the computed 3167-3168 cm-1 X-H band to the observed 3095 cm-1 feature; the caption states it was adjusted to fit the experiment (Table 1).
  • Mode classification thresholds (planarity, OOP amplitude, X-H dot product) = 1 Å, 0.9, 0.2 Å
    Hand-chosen constants in Section 3.4; no sensitivity analysis is given and they are validated only on pyrene, naphthalene, and ovalene.
  • Matching thresholds tau_deltanu and tau_I = 30 cm-1 and 0.03
    Default thresholds of the matching algorithm (Eqs. (4) and (5)); user-adjustable and chosen without stated calibration.
  • Lorentzian half-width w and zero-zero shift = user-tuned
    Line shape width is seeded from the experimental spectrum and both parameters are tuned by eye during the demo (Sections 3.6 and 5).
assumptions (5)
  • domain assumption Franck-Condon and Herzberg-Teller approximations yield reliable relative vibronic intensities
    Adopted from Sections 2.2.1 to 2.2.3; the tool consumes FC/HT intensities from Gaussian's fcht implementation without independent validation.
  • domain assumption Born-Oppenheimer and harmonic models with Duschinsky rotation are adequate for the target molecules
    Sections 2.2.2 and 2.2.4; the accuracy of the entire comparison depends on the computed stick spectra being close to experiment.
  • domain assumption Anharmonicity is systematic and can be captured by linear per-mode-type scaling of harmonic wavenumbers
    Section 2.2.5 and Eq. (3); this is the standard scaling-factor heuristic that the headline feature automates.
  • domain assumption Gaussian .log files are parsed without loss, including displacement vectors at default two-decimal precision
    Sections 3.2 and 4.2; low-precision displacement vectors underpin the OOP and X-H classification thresholds.
  • standard math Standard numerical methods (Lorentzian convolution, moving-average smoothing, local-maximum detection) behave as implemented
    Sections 2.2.6, 4.3, and 4.4; the correctness of Eq. (2) and the detected peak lists depends on these routines.

how reviews work

0 comments
Cite this review

Pith. "Pith review of SpectraMatcher: A Python Program for Interactive Analysis and Peak Assignment of Vibronic Spectra." pith.science (2026). https://pith.science/paper/32FWS6TP

@misc{pith2026250509060,
  author       = {Pith},
  title        = {Pith review of: SpectraMatcher: A Python Program for Interactive Analysis and Peak Assignment of Vibronic Spectra},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/32FWS6TP}},
  note         = {Machine review of arXiv:2505.09060}
}
read the original abstract

SpectraMatcher is a cross-platform desktop application for interactive comparison of experimental and computed vibronic spectra, designed to assist in the recognition and assignment of spectral patterns. It provides an intuitive graphical interface -- with no coding or scripting required -- for importing experimental spectra, visualizing them alongside the corresponding theoretical spectra constructed from Gaussian frequency calculations, and adjusting key parameters such as peak width, intensity scaling factors, and vibration-type-specific anharmonic corrections. SpectraMatcher features an automated peak-matching algorithm that assigns experimental and computed peaks based on their intensity ratio and proximity. Assignments and spectra can be exported in multiple formats for publication or for further analysis. The software remains responsive even for large datasets, and supports efficient and reproducible interpretation of vibronic spectra.

Figures

Figures reproduced from arXiv: 2505.09060 by the authors.

Figure 1
Figure 1. Franck–Condon diagram illustrating vertical excitation from [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Comparison of the experimental emission spectrum of ovalene (bot [PITH_FULL_IMAGE:figures/full_fig_p010_2.png] view at source ↗
Figure 3
Figure 3. Experimental excitation spectrum of ovalene (bottom) and simulated [PITH_FULL_IMAGE:figures/full_fig_p011_3.png] view at source ↗

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

82 extracted references · 58 canonical work pages

  1. [36]

    Weber, J

    I. Weber, J. Langner, H. A. Witek, Y .-P. Lee, Electronic spectroscopy of ovalene: Reassignment of the S2(B3u)– S0(Ag) transition, J. Phys. Chem. Lett. 15 (42) (2024) 10696–10702. doi:10.1021/acs.jpclett. 4c02494

    doi:10.1021/acs.jpclett 2024

  2. [1]

    Hodecker, M

    M. Hodecker, M. Biczysko, A. Dreuw, V . Barone, Simulation of vacuum UV absorption and electronic circular dichroism spectra of methyl oxi- rane: The role of vibrational effects, J. Chem. Theory Comput. 12 (2016) 2820–2833. doi:10.1021/acs.jctc.6b00121

    work page doi:10.1021/acs.jctc.6b00121 2016

  3. [2]

    Y . Qian, X. Li, A. Harutyunyan, G. Chen, Y . Rao, H. Chen, Herzberg– Teller effect on the vibrationally resolved absorption spectra of single- crystalline pentacene at finite temperatures, J. Phys. Chem. A 124 (2020) 9156–9165. doi:10.1021/acs.jpca.0c07896

    work page doi:10.1021/acs.jpca.0c07896 2020

  4. [3]

    Plakhotnik, T

    T. Plakhotnik, T. Nonn, V . Palm, Saturation spectroscopy of vibronic transitions in single molecules, Chem. Phys. Lett. 357 (2002) 397–402. doi:10.1016/S0009-2614(02)00497-9

    work page doi:10.1016/s0009-2614(02)00497-9 2002

  5. [4]

    P. B. Crandall, D. M ¨uller, J. Leroux, M. F¨orstel, O. Dopfer, Optical spec- trum of the adamantane radical cation, Astrophys. J. Lett. 900 (2) (2020) L20. doi:10.3847/2041-8213/abafbd

    work page doi:10.3847/2041-8213/abafbd 2020

  6. [5]

    Zirkelbach, M

    J. Zirkelbach, M. Mirzaei, I. Deperasinska, B. Kozankiewicz, B. Gurlek, A. Shkarin, T. Utikal, S. G ¨otzinger, V . Sandoghdar, High-resolution vi- bronic spectroscopy of a single molecule embedded in a crystal, J. Chem. Phys. 156 (2022) 104301. doi:10.1063/5.0081297

    work page doi:10.1063/5.0081297 2022

  7. [6]

    C. Loe, S. Chatterjee, R. B. Weakly, M. Khalil, Observing vibronic cou- pling in a strongly hydrogen bonded system with coherent multidimen- sional vibrational–electronic spectroscopy, J. Chem. Phys. 161 (2024) 174203. doi:10.1063/5.0226236

    doi:10.1063/5.0226236 2024

  8. [7]

    Ruiterkamp, T

    R. Ruiterkamp, T. Halasinski, F. Salama, B. Foing, L. Allamandola, W. Schmidt, P. Ehrenfreund, Spectroscopy of large PAHs, Astronomy & Astrophysics 390 (2002) 1153–1170. doi:10.1051/0004-6361: 20020478

    doi:10.1051/0004-6361: 2002

Show all 82 references
  1. [8]

    Hoheisel, A

    G. Hoheisel, A. Hese, High resolution laser induced fluorescence excita- tion spectroscopy of jet-cooled terrylene, J. Mol. Spectrosc. 235 (2006) 211–217. doi:10.1016/j.jms.2005.11.007

    2006 doi

  2. [9]

    Banasiewicz, J

    M. Banasiewicz, J. Dresner, O. Morawski, D. Wicek, B. Kozankiewicz, Purely electronic and vibronic fluorescence excitation of single terrylene molecules in a naphthalene crystal, Acta Phys. Pol. A 112 (2007) 85–94. doi:10.12693/APhysPolA.112.S-85

    2007 doi

  3. [10]

    Makarewicz, I

    A. Makarewicz, I. Deperasi ´nska, E. Karpiuk, J. Nowacki, B. Kozankiewicz, Vibronic spectra of single dibenzoterrylene molecules in anthracene and 2,3-dimethylanthracene crystals, Chem. Phys. Lett. 535 (2012) 140–145. doi:10.1016/j.cplett.2012.03.091

    2012 doi

  4. [11]

    Auerswald, B

    J. Auerswald, B. Engels, I. Fischer, T. Gerbich, J. Herterich, A. Krueger, M. Lang, H.-C. Schmitt, C. Schon, C. Walter, The electronic structure of pyracene: a spectroscopic and computational study, Phys. Chem. Chem. Phys. 15 (2013) 8151–8161. doi:10.1039/C3CP44271C

    2013 doi

  5. [12]

    C. A. Rice, J. Fulara, I. Garkusha, ´Ad´am Nagy, F.-X. Hardy, O. Gause, J. P. Maier, Electronic spectra of corannulenic cations and neutrals in neon matrices and protonated corannulene in the gas phase at 15 K, Z. Phys. Chem. 229 (2015) 1709–1728. doi:10.1515/zpch-2015-0598

    2015 doi

  6. [13]

    Chakraborty, C

    A. Chakraborty, C. A. Rice, F.-X. Hardy, J. Fulara, J. P. Maier, Electronic spectra of protonated fluoranthene in a neon matrix and gas phase at 10 K, J. Phys. Chem. A 120 (27) (2016) 4805–4811. doi:10.1021/acs. jpca.5b12232

    2016 doi

  7. [14]

    Weber, C.-W

    I. Weber, C.-W. Wang, S.-C. Huang, C.-Y . Zhu, Y .-P. Lee, Fluorescence excitation and dispersed fluorescence spectra of the 1-hydronaphthyl rad- ical (1-C10H9) in solid para-hydrogen, J. Phys. Chem. A 126 (45) (2022) 8423–8433. doi:10.1021/acs.jpca.2c06169

    2022 doi

  8. [15]

    Weber, M

    I. Weber, M. Tsuge, P. Sundararajan, M. Baba, H. Sakurai, Y .-P. Lee, Infrared and laser-induced fluorescence spectra of sumanene isolated in solid para-hydrogen, J. Phys. Chem. A 126 (32) (2022) 5283–5293.doi: 10.1021/acs.jpca.2c02906

    2022 doi

  9. [16]

    Katori, S

    T. Katori, S. Kunishige, M. Baba, N. Nakayama, T. Ishimoto, A. Nishiyama, S. Yamasaki, M. Misono, Electronic, vibrational, and ro- tational analysis of 1,2-benzanthracene by high-resolution spectroscopy referenced to an optical frequency comb, J. Chem. Phys. 157 (23) (2022) 23...

    2022 doi

  10. [17]

    Weber, Y .-P

    I. Weber, Y .-P. Lee, Fluorescence excitation and dispersed fluorescence spectra of the first electronic excited (S1) state of peri-hexabenzocoronene (C42H18) isolated in solid para-hydrogen, J. Phys. Chem. A 128 (25) (2024) 4984–4991. doi:10.1021/acs.jpca.4c02320

    2024 doi

  11. [18]

    Sch ¨afer, S

    A. Sch ¨afer, S. Debnath, J. Tr ¨ankle, T. Mohr, M. M. Kappes, Acriflavine is more than it seems: Resolving optical properties of multiple isomeric constituents at 5 k, J. Phys. Chem. Lett. 15 (28) (2024) 7295–7301. doi: 10.1021/acs.jpclett.4c01517

    2024 doi

  12. [19]

    Van Rossum, F

    G. Van Rossum, F. L. Drake Jr, Python reference manual, Centrum voor Wiskunde en Informatica Amsterdam, 1995

    1995

  13. [20]

    Van Rossum, F

    G. Van Rossum, F. L. Drake, Python 3 Reference Manual, CreateSpace, Scotts Valley, CA, 2009

    2009

  14. [21]

    C. R. Harris, K. J. Millman, S. J. van der Walt, R. Gommers, P. Vir- tanen, D. Cournapeau, E. Wieser, J. Taylor, S. Berg, N. J. Smith, R. Kern, M. Picus, S. Hoyer, M. H. van Kerkwijk, M. Brett, A. Hal- dane, J. F. del R´ıo, M. Wiebe, P. Peterson, P. G´erard-Marchant, K. Shep- ...

    2020 doi

  15. [22]

    Ho ffstadt, P

    J. Ho ffstadt, P. Cothren, S. Mazzi, V . Ein, DearPyGui: A modern, fast and powerful GUI framework for Python, https://github.com/ hoffstadt/DearPyGui (2021)

    2021

  16. [23]

    M. J. Frisch, G. W. Trucks, H. B. Schlegel, G. E. Scuseria, M. A. Robb, J. R. Cheeseman, G. Scalmani, V . Barone, G. A. Petersson, H. Nakatsuji, X. Li, M. Caricato, A. V . Marenich, J. Bloino, B. G. Janesko, R. Gom- perts, B. Mennucci, H. P. Hratchian, J. V . Ortiz, A. F. Izma...

    2016

  17. [24]

    Franck, E

    J. Franck, E. G. Dymond, Elementary processes of photochemical reac- tions, J. Chem. Soc. Faraday Trans. 21 (1926) 536–542. doi:10.1039/ TF9262100536

    1926

  18. [25]

    Condon, A Theory of Intensity Distribution in Band Systems, Phys

    E. Condon, A Theory of Intensity Distribution in Band Systems, Phys. Rev. 28 (6) (1926) 1182–1201. doi:10.1103/PhysRev.28.1182

    1926 doi

  19. [26]

    Herzberg, E

    G. Herzberg, E. Teller, Schwingungsstruktur der Elektronen¨uberg¨ange bei mehratomigen Molek¨ulen, Z. Phys. Chem. 21B (1) (1933) 410–446, pub- lisher: De Gruyter (O). doi:10.1515/zpch-1933-2136

    1933 doi

  20. [27]

    Barone, J

    V . Barone, J. Bloino, M. Biczysko, F. Santoro, Fully integrated approach to compute vibrationally resolved optical spectra: From small molecules to macrosystems, J. Chem. Theory Comput. 5 (3) (2009) 540–554. doi: 10.1021/ct8004744

    2009 doi

  21. [28]

    J. A. Pople, H. B. Schlegel, R. Krishnan, D. J. Defrees, J. S. Binkley, M. J. Frisch, R. A. Whiteside, R. F. Hout, W. J. Hehre, Molecular orbital studies of vibrational frequencies, Int. J. Quantum Chem. 20 (S15) (1981) 269–278. doi:https://doi.org/10.1002/qua.560200829

    1981 doi

  22. [29]

    A. P. Scott, L. Radom, Harmonic vibrational frequencies: An evalua- tion of Hartree–Fock, Møller–Plesset, quadratic configuration interaction, density functional theory, and semiempirical scale factors, J. Phys. Chem. 100 (41) (1996) 16502–16513. doi:10.1021/jp960976r

    1996 doi

  23. [30]

    Sinha, S

    P. Sinha, S. E. Boesch, C. Gu, R. A. Wheeler, A. K. Wilson, Harmonic vibrational frequencies: Scaling factors for HF, B3LYP, and MP2 meth- ods in combination with correlation consistent basis sets, J. Phys. Chem. A 108 (42) (2004) 9213–9217. doi:10.1021/jp048233q

    2004 doi

  24. [31]

    K. K. Irikura, R. D. I. Johnson, R. N. Kacker, R. Kessel, Uncertainties in scaling factors for ab initio vibrational zero-point energies, J. Chem. Phys. 130 (11) (2009) 114102. doi:10.1063/1.3086931

    2009 doi

  25. [32]

    R. L. Jacobsen, R. D. I. Johnson, K. K. Irikura, R. N. Kacker, Anhar- monic vibrational frequency calculations are not worthwhile for small basis sets, J. Chem. Theory Comput. 9 (2) (2013) 951–954. doi: 10.1021/ct300293a

    2013 doi

  26. [33]

    Herzberg, Molecular Spectra and Molecular Structure, 2nd Edition, D

    G. Herzberg, Molecular Spectra and Molecular Structure, 2nd Edition, D. Van Nostrand, New York, 1950

    1950

  27. [34]

    C. N. Banwell, E. M. McCash, Fundamentals of Molecular Spectroscopy, 4th Edition, McGraw-Hill, 1994

    1994

  28. [35]

    Atkins, J

    P. Atkins, J. de Paula, Physical Chemistry, 7th Edition, Oxford University Press, 2002

    2002

  29. [37]

    M. Born, R. Oppenheimer, Zur Quantentheorie der Molekeln, Ann. Phys. 389 (20) (1927) 457–484. doi:10.1002/andp.19273892002

    1927 doi

  30. [38]

    E. B. Wilson, J. C. Decius, P. C. Cross, Molecular Vibrations: The Theory of Infrared and Raman Vibrational Spectra, Courier Corporation, 1980

    1980

  31. [39]

    E. J. Heller, Time-dependent approach to semiclassical dynamics, J. Chem. Phys. 62 (4) (1975) 1544–1555. doi:10.1063/1.430620

    1975 doi

  32. [40]

    Mukamel, Principles of Nonlinear Optical Spectroscopy, Oxford Uni- versity Press, 1995

    S. Mukamel, Principles of Nonlinear Optical Spectroscopy, Oxford Uni- versity Press, 1995

    1995

  33. [41]

    S. Li, D. Truhlar, Franck–Condon models for simulating the band shape of electronic absorption spectra, J. Chem. Theory Comput. 13 (05 2017). doi:10.1021/acs.jctc.7b00325

    2017 doi

  34. [42]

    Duschinsky, Zur Deutung der Elektronenspektren mehratomiger Molek¨ule, Acta Physicochim

    F. Duschinsky, Zur Deutung der Elektronenspektren mehratomiger Molek¨ule, Acta Physicochim. URSS 7 (1937) 551–566

    1937

  35. [43]

    Santoro, R

    F. Santoro, R. Improta, A. Lami, J. Bloino, V . Barone, Effective method to compute Franck–Condon integrals for optical spectra of large molecules in solution, J. Chem. Phys. 126 (8) (2007) 084509. doi:10.1063/1. 2437197

    2007 doi

  36. [44]

    Barone, J

    V . Barone, J. Bloino, M. Biczysko, F. Santoro, Fully Integrated Ap- proach to Compute Vibrationally Resolved Optical Spectra: From Small Molecules to Macrosystems, J. Chem. Theory Comput. 5 (3) (2009) 540–554, publisher: American Chemical Society. doi:10.1021/ ct8004744

    2009

  37. [45]

    P. M. Morse, Diatomic Molecules According to the Wave Mechanics. II. Vibrational Levels, Phys. Rev. 34 (1) (1929) 57–64, publisher: American Physical Society. doi:10.1103/PhysRev.34.57

    1929 doi

  38. [46]

    Temelso, G

    B. Temelso, G. C. Shields, The role of anharmonicity in hydrogen-bonded systems: The case of water clusters, J. Chem. Theory Comput. 7 (2011) 2804–2817. doi:10.1021/ct2003308

    2011 doi

  39. [47]

    R. J. Le Roy, N. S. Dattani, J. A. Coxon, A. J. Ross, P. Crozet, C. Linton, Accurate analytic potentials for Li 2(X1Σ+ g ) and Li 2(A1Σ+ u ) from 2 to 90 Å, and the radiative lifetime of Li(2p), J. Chem. Phys. 131 (20) (2009) 204309. doi:10.1063/1.3264688

    2009 doi

  40. [48]

    Qadeer, G

    S. Qadeer, G. D. Santis, P. Stinis, S. S. Xantheas, Vibrational levels of a generalized morse potential, J. Chem. Phys. 157 (14) (2022) 144104. doi:10.1063/5.0103433

    2022 doi

  41. [49]

    Quack, M

    M. Quack, M. A. Suhm, Potential energy surfaces, quasiadiabatic chan- nels, rovibrational spectra, and intramolecular dynamics of (HF) 2 and its isotopomers from quantum Monte Carlo calculations, J. Chem. Phys. 95 (1) (1991) 28–59. doi:10.1063/1.461486

    1991 doi

  42. [50]

    Vendrell, F

    O. Vendrell, F. Gatti, D. Lauvergnat, H.-D. Meyer, Full-dimensional (15-dimensional) quantum-dynamical simulation of the protonated water dimer. I. Hamiltonian setup and analysis of the ground vibrational state, J. Chem. Phys. 127 (18) (2007) 184302. doi:10.1063/1.2787588

    2007 doi

  43. [51]

    D. H. Zhang, Q. Wu, J. Z. H. Zhang, M. von Dirke, Z. Ba ˇci´c, Exact full-dimensional bound state calculations for (HF)2, (DF)2, and HFDF, J. Chem. Phys. 102 (6) (1995) 2315–2325. doi:10.1063/1.468719

    1995 doi

  44. [52]

    Vendrell, F

    O. Vendrell, F. Gatti, H.-D. Meyer, Full dimensional (15-dimensional) quantum-dynamical simulation of the protonated water dimer. II. In- frared spectrum and vibrational dynamics, J. Chem. Phys. 127 (18) (2007) 184303. doi:10.1063/1.2787596

    2007 doi

  45. [53]

    J. M. Bowman, Self-consistent field energies and wavefunctions for cou- pled oscillators, J. Chem. Phys. 68 (2) (1978) 608–610. doi:10.1063/ 1.435782

    1978

  46. [54]

    G. M. Chaban, J. O. Jung, R. B. Gerber, Ab initio calculation of anhar- monic vibrational states of polyatomic systems: Electronic structure com- bined with vibrational self-consistent field, J. Chem. Phys. 111 (5) (1999) 1823–1829. doi:10.1063/1.479452

    1999 doi

  47. [55]

    J. M. Bowman, C. Tucker, H.-D. Meyer, Variational quantum approaches for computing vibrational energies of polyatomic molecules, Mol. Phys. 106 (16-18) (2008) 2145–2182. doi:10.1080/00268970802258609

    2008 doi

  48. [56]

    Christiansen, Selected new developments in vibrational structure the- ory: Potential construction and vibrational wave function calculations, Phys

    O. Christiansen, Selected new developments in vibrational structure the- ory: Potential construction and vibrational wave function calculations, Phys. Chem. Chem. Phys. 14 (19) (2012) 6672–6687. doi:10.1039/ C2CP40090A

    2012

  49. [57]

    Meyer, U

    H.-D. Meyer, U. Manthe, L. S. Cederbaum, The multi-configurational time-dependent Hartree approach, Chem. Phys. Lett. 165 (1) (1990) 73–

    1990

  50. [58]

    J. M. Bowman, S. Carter, X. H. and, Multimode: A code to calculate rovibrational energies of polyatomic molecules, Int. Rev. Phys. Chem. 22 (3) (2003) 533–549. doi:10.1080/0144235031000124163

    2003 doi

  51. [59]

    H.-G. Yu, S. Ndengue, J. Li, R. Dawes, H. Guo, Vibrational energy lev- els of the simplest Criegee intermediate (CH2OO) from full-dimensional Lanczos, MCTDH, and MULTIMODE calculations, J. Chem. Phys. 143 (8) (2015) 084311. doi:10.1063/1.4929707

    2015 doi

  52. [60]

    Nishimura, Y .-P

    Y . Nishimura, Y .-P. Lee, S. Irle, H. A. Witek, Critical interpretation of CH– and OH– stretching regions for infrared spectra of methanol clus- ters (CH3OH)n (n = 2–5) using self-consistent-charge density functional tight-binding molecular dynamics simulations, J. Chem. Phys...

    2014 doi

  53. [61]

    Cheng, R

    X. Cheng, R. P. Steele, E fficient anharmonic vibrational spectroscopy for large molecules using local-mode coordinates, J. Chem. Phys. 141 (10) (2014) 104105. doi:10.1063/1.4894507

    2014 doi

  54. [62]

    P. T. Panek, C. R. Jacob, Anharmonic theoretical vibrational spectroscopy of polypeptides, J. Phys. Chem. Lett. 7 (16) (2016) 3084–3090. doi: 10.1021/acs.jpclett.6b01451

    2016 doi

  55. [63]

    Ceotto, S

    M. Ceotto, S. Atahan, G. F. Tantardini, A. Aspuru-Guzik, Multiple co- herent states for first-principles semiclassical initial value representation molecular dynamics, J. Chem. Phys. 130 (23) (2009) 234113. doi: 10.1063/1.3155062

    2009 doi

  56. [64]

    Conte, A

    R. Conte, A. Aspuru-Guzik, M. Ceotto, Reproducing deep tunneling split- tings, resonances, and quantum frequencies in vibrational spectra from a 13 handful of direct ab initio semiclassical trajectories, J. Phys. Chem. Lett. 4 (20) (2013) 3407–3412. doi:10.1021/jz401603f

    2013 doi

  57. [65]

    Aieta, M

    C. Aieta, M. Micciarelli, G. Bertaina, M. Ceotto, Anharmonic quantum nuclear densities from full dimensional vibrational eigenfunctions with application to protonated glycine, Nat. Commun. 11 (1) (2020) 4348. doi:10.1038/s41467-020-18211-3

    2020 doi

  58. [66]

    Barone, Anharmonic vibrational properties by a fully automated second-order perturbative approach, J

    V . Barone, Anharmonic vibrational properties by a fully automated second-order perturbative approach, J. Chem. Phys. 122 (1) (2005) 014108. doi:10.1063/1.1824881

    2005 doi

  59. [67]

    Alcolea Palafox, DFT computations on vibrational spectra: Scaling procedures to improve the wavenumbers, Phys

    M. Alcolea Palafox, DFT computations on vibrational spectra: Scaling procedures to improve the wavenumbers, Phys. Sci. Rev. 3 (6) (2018) 20170184. doi:https://doi.org/10.1515/psr-2017-0184

    2018 doi

  60. [68]

    R. S. Grev, C. L. Janssen, H. F. I. Schaefer, Concerning zero-point vi- brational energy corrections to electronic energies, J. Chem. Phys. 95 (7) (1991) 5128–5132. doi:10.1063/1.461680

    1991 doi

  61. [69]

    Barone, Vibrational zero-point energies and thermodynamic functions beyond the harmonic approximation, J

    V . Barone, Vibrational zero-point energies and thermodynamic functions beyond the harmonic approximation, J. Chem. Phys. 120 (7) (2004) 3059–3065. doi:10.1063/1.1637580

    2004 doi

  62. [70]

    C. W. Bauschlicher, S. R. Langhoff, The calculation of accurate harmonic frequencies of large molecules: the polycyclic aromatic hydrocarbons, a case study, Spectrochim. Acta, Part A 53 (1997) 1225–1240

    1997

  63. [71]

    R. D. I. Johnson, K. K. Irikura, R. N. Kacker, R. Kessel, Scaling fac- tors and uncertainties for ab initio anharmonic vibrational frequencies, J. Chem. Theory Comput. 6 (9) (2010) 2822–2828. doi:10.1021/ ct100244d

    2010

  64. [72]

    H. A. Witek, K. Morokuma, Systematic study of vibrational frequencies calculated with the self-consistent charge density functional tight-binding method, J. Comput. Chem. 25 (15) (2004) 1858–1864. doi:https:// doi.org/10.1002/jcc.20112

    2004 doi

  65. [73]

    J. P. Merrick, D. Moran, L. Radom, An evaluation of harmonic vibrational frequency scale factors, J. Phys. Chem. A 111 (45) (2007) 11683–11700. doi:10.1021/jp073974n

    2007 doi

  66. [74]

    I. M. Alecu, J. Zheng, Y . Zhao, D. G. Truhlar, Computational thermo- chemistry: Scale factor databases and scale factors for vibrational fre- quencies obtained from electronic model chemistries, J. Chem. Theory Comput. 6 (9) (2010) 2872–2887. doi:10.1021/ct100326h

    2010 doi

  67. [75]

    R. D. I. Johnson, Vibrational frequency scale factors, https://cccbdb. nist.gov/vsfx.asp, NIST Computational Chemistry Comparison and Benchmark Database (CCCBDB) (1998)

    1998

  68. [76]

    Yoshida, K

    H. Yoshida, K. Takeda, J. Okamura, A. Ehara, H. Matsuura, A new ap- proach to vibrational analysis of large molecules by density functional theory: Wavenumber-Linear Scaling method, J. Phys. Chem. A 106 (14) (2002) 3580–3586. doi:10.1021/jp013084m

    2002 doi

  69. [77]

    S. Hony, C. Van Kerckhoven, E. Peeters, A. G. G. M. Tielens, D. M. Hudgins, L. J. Allamandola, The CH out-of-plane bending modes of PAH molecules in astrophysical environments, Astronomy & Astrophysics 370 (2001) 1030–1043. doi:10.1051/0004-6361:20010242

    2001 doi

  70. [78]

    doi:https://doi.org/10.1016/0009-2614(90)87014-I

    doi

  71. [79]

    Hayen, Nuitka, https://github.com/Nuitka/Nuitka (2025)

    K. Hayen, Nuitka, https://github.com/Nuitka/Nuitka (2025)

    2025

  72. [80]

    Virtanen, R

    P. Virtanen, R. Gommers, T. E. Oliphant, M. Haberland, T. Reddy, D. Cournapeau, E. Burovski, P. Peterson, W. Weckesser, J. Bright, S. J. van der Walt, M. Brett, J. Wilson, K. J. Millman, N. Mayorov, A. R. J. Nelson, E. Jones, R. Kern, E. Larson, C. J. Carey,˙I. Polat, Y . Feng...

    2020

  73. [81]

    Amirav, U

    A. Amirav, U. Even, J. Jortner, Intermediate level structure in the S 2 state of the isolated ultracold ovalene molecule, Chem. Phys. Lett. 69 (1) (1980) 14–17. doi:10.1016/0009-2614(80)80003-0

    1980 doi

  74. [82]

    Amirav, U

    A. Amirav, U. Even, J. Jortner, Excited-state dynamics of the isolated ultracold ovalene molecule, J. Chem. Phys. 74 (7) (1981) 3745–3756. doi:10.1063/1.441603. 14

    1981 doi

Pith tools

Reviewed August 15, 2026 · model on record in the stance chip above.